Nonlinear Impairment Compensation using Neural Networks

Publication Date: 6/7/2021

Event: OFC 2021

Reference: M5F.1: 1-3, 2021

Authors: Shinsuke Fujisawa, NEC Laboratories America, Inc.; Fatih Yaman, NEC Laboratories America, Inc.; Hussam G. Batshon, NEC Laboratories America, Inc.; Massaki Tanio, NEC Corporation; Naoto Ishii, NEC Corporation; Chaoran Huang, Princeton University; Thomas Ferreira de Lima, Princeton University; Yoshihisa Inada, NEC Corporation; Paul R. Prucnal, Princeton University; Norifumi Kamiya, NEC Corporation; Ting Wang, NEC Laboratories America, Inc.

Abstract: Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.

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